StatSnowball: a statistical approach to extracting entity relationships

Traditional relation extraction methods require pre-specified relations and relation-specific human-tagged examples. Bootstrapping systems significantly reduce the number of training examples, but they usually apply heuristic-based methods to combine a set of strict hard rules, which limit the ability to generalize and thus generate a low recall. Furthermore, existing bootstrapping methods do not perform open information extraction (Open IE), which can identify various types of relations without requiring pre-specifications. In this paper, we propose a statistical extraction framework called Statistical Snowball (StatSnowball), which is a bootstrapping system and can perform both traditional relation extraction and Open IE. StatSnowball uses the discriminative Markov logic networks (MLNs) and softens hard rules by learning their weights in a maximum likelihood estimate sense. MLN is a general model, and can be configured to perform different levels of relation extraction. In Sta...

• Type: Conference
• Year: 2009
• Where: WWW
• Authors: Jun Zhu, Zaiqing Nie, Xiaojiang Liu, Bo Zhang, Ji-Rong Wen
• Keywords: Internet Technology, Relation Extraction, Relation Extraction Methods, Traditional Relation Extraction, WWW 2009